Epidemiological and Genetic Studies of Body Mass Index

描述（由申请人提供）：体重指数（BMI）水平升高 与心血管疾病的死亡率和发病率增加有关 疾病、高血压、糖尿病和其他疾病。肥胖的频率 在美国，与此相关的健康问题正在增加， 人口我们建议确定与增加的DNA多态性相关的DNA多态性。 BMI，目的是确定与肥胖有关的基因。应用 建立在NHLBI家族心脏中进行的BMI两阶段基因组扫描的基础上 研究（FHS）。首先，我们检查了101个家系，1027人 基因分型，发现7号染色体上的LOD为2.2。在第二阶段，我们检查了135个 同胞，380人，并发现同一位点的LOD为3.2。引人注目 联合研究发现连锁关系（LOD = 4.9，chr 7q31.3，137 cM）。 确定负责BMI等复杂性状的基因已经证明 非常困难我们提出了一种结合三种切割的新颖策略 边缘方法：（1）回归树分析，以确定一个同质子集 有证据表明BMI与7q31.3相关的家庭;（2）样本的DNA合并 从连锁与非连锁家庭;和（3）定量PCR的DNA池， 高密度SNP作图。我们相信这些方法的结合 将允许一种成本有效的方法来识别遗传 多态性与BMI连锁不平衡，并有可能 成为一种广泛采用的复杂性状基因定位方法。成员 我们的调查团队在设计回归中发挥了主导作用 确定连锁族齐次子集的树方法， 基于人体测量、生活方式和生理因素的差异。 该策略旨在将家庭按病因最佳地划分为 齐次子群的递归划分，定义在 联系信号的强度。递归分区技术 显着增加的权力，以检测链接的样本大小，如 FHS。用于DNA合并和等位基因频率定量的方法，通过质谱分析 光谱学对我们的应用同样重要。使用200个DNA池 每个样本，池将创建从组肥胖和组 来自显示与7q31.3连锁的证据的家庭的非肥胖个体 位点，并将这些与肥胖和非肥胖个体的池进行对比， 没有证据表明有关联的家庭。因为一个单一的PCR反应 代表了对200名研究参与者的分析， 在20至40 Mb的区域中每50 Kb一个SNP变得容易实现。我们 我相信这一应用有潜力开发基因治疗的方法学， BMI和其他复杂性状的定位和鉴定。

DESCRIPTION (provided by applicant): Increased levels of Body Mass Index (BMI) are associated with increased mortality and morbidity from cardiovascular disease, hypertension, diabetes and other disorders. The frequency of obesity and its associated health-related problems is increasing in the American population. We propose to identify DNA polymorphisms associated with increased BMI, with the goal of identifying genes involved in obesity. The application builds upon a two-stage genome scan for BMI performed in the NHLBI Family Heart Study (FHS). In the first, we examined 101 pedigrees with 1027 persons genotyped and found a LOD of 2.2 on chromosome 7. In stage 2 we examined 135 sibships, 380 persons, and found a LOD of 3.2 for the same locus. Compelling linkage was found in the combined study (LOD = 4.9, chr 7q31.3, 137cM). Identifying genes responsible for complex traits such as BMI has proven remarkably difficult. We propose a novel strategy which combines three cutting edge methods: (1) Regression Tree analyses to identify a homogenous subset of families with evidence for BMI linkage to 7q31.3; (2) DNA pooling of samples from linked versus unlinked families; and (3) quantitative PCR of DNA pools for very high-density SNP mapping. We believe that the combination of these methods will permit a cost effective approach for the identification of genetic polymorphisms in linkage disequilibrium with BMI, and has the potential to become a widely adopted method for gene localization of complex traits. Members of our investigative team have taken a lead role in designing the Regression Tree method for the identification of homogeneous subsets of linked families, based upon differences in anthropometry, lifestyle and physiologic factors. This strategy is designed to optimally divide the families into etiologically homogeneous subgroups by recursive partitioning, defined in terms of the strength of the linkage signal. The recursive partitioning technique dramatically increases power to detect linkage in a sample size such as that of the FHS. Methods for DNA pooling and allele frequency quantification by Mass Spectroscopy are equally fundamental to our application. Using DNA pools of 200 samples each, pools will be created from groups of obese and groups of non-obese individuals from families showing evidence for linkage to the 7q31.3 locus, and contrasting these with pools of obese and non-obese individuals in families that do not show evidence of linkage. Because a single PCR reaction represents the analysis of 200 study participants, fine mapping at a density of one SNP per 50Kb across a region of 20 to 40 Mb becomes readily achievable. We believe that this application has potential to develop methodologies for gene localization and identification for BMI and other complex traits.